Most Predictable Running Back Stats

TJ is a former full-time poker player who has been playing fantasy football for more than a decade. After online poker was outlawed, TJ ended his poker career and dedicated himself to fantasy football. His background in poker statistics and analytics translates to success in both daily and season-long fantasy football.

This study will shed light on which commonly cited previous-year stats for running backs are reliable indicators of future performance—and which stats can be misleading.

This article has been updated to reflect data through 2017.

The Methodology

In order to keep this study somewhat controlled, only running backs from 2010 on who saw at least 100 touches and remained on the same team in consecutive years were considered. Many variables change from year to year in the NFL, and since a study like this can be inherently sensitive to outliers, eliminating something as drastic as a team change should remove some noise. One hundred touches is an arbitrary cutoff, but an average of 12 or more touches per game over half of a season should be sufficient enough of a sample to reflect a player's true performance level.

This methodology offers us a sample of 185 instances in which a running back met the volume threshold in consecutive seasons for the same team.

The One Type of Stat With the Strongest Correlation

The following table gives the correlations for 17 statistics that are commonly cited when trying to project a running back's upcoming season:

Year-to-Year Statistical Correlations for RBs on Same Team in Consecutive Seasons (since 2010, min. 100 touches)

Stats

Year-to-Year Correlation

Attempts/Game

0.60

Rush Yards/Game

0.58

Touches/Game

0.56

Targets/Game

0.55

Total Yards/Game

0.51

PPR FP/Game

0.49

Total Targets

0.47

Total Receptions

0.47

Total Attempts

0.44

Rushing Yards

0.39

Total Touches

0.36

Total PPR FP

0.30

Total Yards

0.30

Total TD

0.28

Yards/Touch

0.24

Yards/Carry

0.04

Games Played

-0.03

As with the other positions in this series, it's no surprise per-game stats have the strongest year-to-year correlations when you consider they simply represent a player's average performance. On the other hand, volume stats will fluctuate if a player misses a handful of games (and how many games a player plays has virtually no correlation from one year to the next).

Running Backs Need the Ball

A running back’s per-game usage is the most reliable data when trying to project his current season based on the previous year's stats. Running back production is mostly volume-driven—the year-to-year correlation for yards and fantasy scoring is only moderately strong. PPR scoring somewhat mitigates the effect of touchdowns on the bottom-line fantasy scoring, so it makes sense a running back can have a consistent year-to-year fantasy output despite almost no correlation in touchdowns from one year to the next.

Although there is some correlation in per-game production overall from year to year, the correlation isn’t so strong that we can look at the previous season and think that a running back can easily replicate his numbers.

Per-Play Efficiency Can Fool You

The unreliability of efficiency metrics (yards per touch and yards per carry) is perhaps the biggest data point to note.

Touchdowns are generally known to be the most volatile stat (and therefore the hardest to predict), but we should also exercise caution when using a back's previous-year per-touch data as a reference point for projections.

Consider LeSean McCoy—one of the more consistent fantasy running backs in recent history—and his yearly yards per carry from 2010 through 2017:

McCoy's range of outcomes may seem relatively small, but assuming a 300-carry season, the difference between McCoy’s best and worst yards per touch figure would result in a gap of roughly 400 yards. Even the most consistent fantasy scorers are susceptible to large swings in efficiency from season to season.

Efficiency metrics, as I've mentioned in my previous work, are perhaps best used to compare a player's end-of-season numbers to the league average, or to his individual average (if the sample is large enough). You can then decide to what extent regression to the mean should be expected.

The Bottom Line

When analyzing the previous season's running back stats, here's what to keep in mind: